Robust drift characterization from event streams of business processes

A Ostovar, SJJ Leemans, ML Rosa

ACM Transactions on Knowledge Discovery from Data | Association for Computing Machinery | Published : 2020


Business processes are prone to change and evolution. Process workers often change the execution of a process in order to adjust to changes in their operational environment, e.g. changes in workload, season or regulations. These process changes are often undocumented and over time may negatively affect process performance. As such, several techniques have been developed for detecting process changes, a.k.a. process drifts, from event logs and event streams, recording the executions of a process. However, detecting a drift without providing explanations on its nature, a.k.a. drift characterization, is not enough to help analysts understand and rectify process performance issues. The existing..

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